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Hierarchical vectorization of electrical drawings in document images by connectivity analysis of symbols and super-components

机译:符号和超组件连接分析文档图像中电气图的层次矢量化

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Abstract A novel integrated technique is proposed for hierarchical vectorization of electrical drawings in document images. Its first step includes recognition of different electrical symbols and their interconnections based on morphological operations and geometric analysis in three well-distinguished subspaces. This is followed by a hierarchical analysis for detecting the (series-or parallel-connected) super-components in an iterative manner. Finally a compact collection of circuit adjacency lists is produced, which are reduced further by binary encoding. Reconstruction algorithm has also been explained to merit the overall efficacy of the vectorization. Experimental results have been furnished to demonstrate its efficiency and robustness.
机译:<标题>抽象 ara>提出了一种新的集成技术,用于文档图像中的电气图形的分层矢量化。 其第一步包括基于三个良好的子空间中的形态学操作和几何分析来识别不同的电符号及其互连。 其次是以迭代方式检测(系列 - 或并行连接)超组件的分层分析。 最后产生电路邻接列表的紧凑集合,通过二进制编码进一步减少。 还探讨了重建算法以优异的效果。 实验结果已经提供展示其效率和鲁棒性。

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